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Do measures of reactive balance control predict falls in people with stroke returning to the community? A. Mansfield a,b,c,∗ , J.S. Wong a,b , W.E. McIlroy a,b,c,d , L. Biasin a,b , K. Brunton a,b , M. Bayley a,b,c , E.L. Inness a,b a
Toronto Rehabilitation Institute–University Health Network, Toronto, ON, Canada b University of Toronto, Toronto, ON, Canada c Sunnybrook Health Sciences Centre, Toronto, ON, Canada d University of Waterloo, Waterloo, ON, Canada
Abstract Objective To determine if reactive balance control measures predict falls after discharge from stroke rehabilitation. Design Prospective cohort study. Setting Rehabilitation hospital and community. Participants Independently ambulatory individuals with stroke who were discharged home after inpatient rehabilitation (n = 95). Main outcome measures Balance and gait measures were obtained from a clinical assessment at discharge from inpatient stroke rehabilitation. Measures of reactive balance control were obtained: (1) during quiet standing; (2) when walking; and (3) in response to large postural perturbations. Participants reported falls and activity levels up to 6 months post-discharge. Logistic and Poisson regressions were used to identify measures of reactive balance control that were related to falls post-discharge. Results Decreased paretic limb contribution to standing balance control [rate ratio 0.8, 95% confidence interval (CI) 0.7 to 1.0; P = 0.011], reduced between-limb synchronisation of quiet standing balance control (rate ratio 0.9, 95% CI 0.8 to 0.9; P < 0.0001), increased step length variability (rate ratio 1.4, 95% CI 1.2 to 1.7; P = 0.0011) and inability to step with the blocked limb (rate ratio 1.2, 95% CI 1.0 to 1.3; P = 0.013) were significantly associated with increased fall rates when controlling for age, stroke severity, functional balance and daily walking activity. Conclusions Impaired reactive balance control in standing and walking predicted increased risk of falls post-discharge from stroke rehabilitation. Specifically, measures that revealed the capacity of both limbs to respond to instability were related to increased risk of falls. These results suggest that post-stroke rehabilitation strategies for falls prevention should train responses to instability, and focus on remediating dyscontrol in the more-affected limb. © 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.
Keywords: Accidental falls; Stroke; Rehabilitation; Community; Postural balance
Introduction Risk of falls post-stroke is high; up to 73% of communitydwelling stroke survivors fall in the 6 months after discharge from hospital [1]. This suggests that those at greatest risk ∗ Corresponding author. Address: Toronto Rehabilitation Institute–University Health Network, Research–Mobility, 550 University Ave, Room 11-117, Toronto, ON, Canada M5A 2G2. Tel.: +1 416 597 3422x7831; fax: +1 416 597 3031. E-mail address: [email protected] (A. Mansfield).
are not identified or prepared for the challenges they will encounter in their everyday living environments [2]. Individuals with stroke often have impaired balance control, which may increase the risk of falls. While several prospective studies of community-dwelling adults with stroke demonstrated a link between functional balance measures and falls [3–5], other studies found no differences in these balance measures between fallers and non-fallers [6,7]. There are several limitations to existing predictors of falls available to clinicians. Clinical measures typically assign numerical values to varying levels of performance on tasks
http://dx.doi.org/10.1016/j.physio.2015.01.009 0031-9406/© 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.
Please cite this article in press as: Mansfield A, et al. Do measures of reactive balance control predict falls in people with stroke returning to the community? Physiotherapy (2015), http://dx.doi.org/10.1016/j.physio.2015.01.009
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that challenge an individual’s balance, but are neither able to quantify nor reveal the underlying sources of dyscontrol which make that task challenging. A key factor that ultimately determines whether an individual will fall is the ability to react to a loss of balance [8]. Individuals with stroke have impaired reactive balance control (i.e. the ability to execute appropriate and effective reactions to recover from perturbations to balance) [9–12]. This study aimed to determine if measures of reactive balance control (assessed during quiet standing and walking, and in response to external postural perturbations) predict increased risk of falls for stroke survivors returning to community living following discharge from inpatient rehabilitation. It was hypothesised that impaired reactive balance control in quiet standing and walking, and in response to external postural perturbations would be predictive of increased risk of falls, independent of age, stroke severity, daily walking activity or functional balance measures.
Methods Study design This was a prospective cohort study. Participants with stroke were recruited at discharge from inpatient rehabilitation and followed for up to 6 months post-discharge. The study was approved by the Toronto Rehabilitation Institute Research Ethics Board (Ref. TRI REB No.10-043). Participants provided written informed consent prior to participation. Participants Individuals with stroke attending inpatient rehabilitation at the Toronto Rehabilitation Institute were eligible for the study if they were: (1) assessed in a specialised balance clinic at discharge; (2) discharged home; and (3) able to ambulate independently (i.e. without assistance/supervision of another person, with or without a gait aid) at the time of discharge. The clinic assessment was completed as part of routine practice by all individuals who had sufficient physical, communication and cognitive function to complete the assessment (as determined by the primary treating physiotherapist); therefore, no further exclusion criteria were applied. Predictor variables Measures of reactive balance control were obtained from the clinic assessment. Variables focused on three domains: (1) quiet standing, (2) walking and (3) perturbation-evoked reactive stepping. Additional data were obtained from participants’ hospital charts, including age, sex, type of stroke, time post-stroke, affected hemisphere, pre-morbid falls history, National Institutes of Health Stroke Scale [13] scores, and Berg Balance Scale [14] scores. The National Institute of
Health Stroke Scale is an 11-item scale that provides a gross measure of the effects and severity of stroke, with higher scores indicating more severe strokes. Items assess cognition (level of consciousness, orientation and ability to follow commands), gaze, visual fields, facial palsy, gross motor function in the arm and leg, ataxia, sensation, language, speech, and extinction and inattention. The Berg Balance Scale is a 14item observational rating scale that provides a measure of functional anticipatory balance control (rather than reactive balance control). For participants with bilateral stroke, the more-affected side was identified. Quiet standing Participants stood in a standardised foot position [15] with one foot on each of two force plates for 30 seconds, and were asked to stand as still as possible with their eyes open. Forces and moments were recorded from the force plates at 256 Hz and filtered using a 10-Hz low-pass zero phase lag Butterworth filter prior to processing. The anteroposterior and medio-lateral centres of pressure (COP) were calculated for each force plate separately and for both feet combined. The root mean square (RMS) of total anteroposterior and medio-lateral COP were calculated to provide a measure of overall COP variability. The contribution of the paretic limb to balance control was calculated by dividing the RMS of antero-posterior COP under the more-affected limb by the sum of the RMS of antero-posterior COP under each limb [16,17]; a value of 0.5 indicates that both limbs contribute equally to balance control, 0.5 indicates that the more-affected limb contributes more to balance control. Between-limb synchronisation of antero-posterior COP was calculated by determining the correlation coefficient between the left and right antero-posterior COP [18,19]. Antero-posterior COP was used for the contribution and synchronisation measures as individual-limb medio-lateral COP is less meaningful for overall bipedal balance control [20]. Walking Participants walked across a 4-m-long pressure mat at their usual pace without a walking aid (whenever possible). Participants walked across the mat three to five times such that at least 18 footfalls were recorded. Step length, step width and step time were calculated for each step. The standard deviations of step length, width and time were calculated for each limb separately; variability was calculated as the average of the standard deviations for the left and right limbs. Overall walking speed was also calculated. Reactive stepping A lean-and-release system was used to study reactive stepping [9,10,12]. Participants stood in a standardised foot position [15], and wore a belt around their trunks attached to a beam via a cable. Participants leaned forward such that approximately 10% of body weight was supported by the
Please cite this article in press as: Mansfield A, et al. Do measures of reactive balance control predict falls in people with stroke returning to the community? Physiotherapy (2015), http://dx.doi.org/10.1016/j.physio.2015.01.009
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cable. The cable released unexpectedly, causing them to fall forwards; the magnitude of the perturbation was so great that a reactive step was required to regain stability. Participants were supervised closely by a physiotherapist who provided assistance, if necessary, and a safety harness attached to an overhead track was worn such that participants would not fall to the floor. Five trials were completed in each of two conditions: usual response and encouraged use. In the usualresponse condition, there was no constraint on participants’ stepping reactions. The ‘preferred’ limb was the limb used most frequently to initiate stepping in the usual-response condition. In the encouraged-use condition, the preferred limb was blocked by the physiotherapists’ hand or foot to encourage stepping with the non-preferred limb [11]. Trials were video-recorded. For the usual-response condition, the following outcome measures were obtained: frequency of ‘assists’ (i.e. reliance on physiotherapist or harness to prevent a fall); frequency of attempted reach-to-grasp reactions (i.e. participant reached for and grasped the physiotherapist); number of steps taken to recover balance; and frequency of ‘slide’ steps (i.e. the initial step involved foot movement without lifting the foot completely off the ground [10]). For the encourageduse condition, the frequency of trials in which the participant attempted to step with the blocked limb was determined. Falls and daily activity Participants completed a 6-month falls monitoring period following discharge from inpatient rehabilitation. Participants used fortnightly calendars printed on pre-stamped postcards to indicate if they experienced a fall or near fall each day, and these were mailed back to the study investigators when each calendar was complete. Participants received a monthly study newsletter as a reminder to return their postcards. If participants failed to return a postcard, a research assistant called them to ascertain if they had fallen in the previous 2 weeks. A fall was defined as ‘an event that results in a person coming to rest unintentionally on the ground or other lower level’ [21]. Falls that occurred due to fainting or loss of consciousness were excluded from analysis. Participants who reported a fall or near fall were asked to call the research assistant to complete a short telephone questionnaire in order to determine the circumstances surrounding the fall or near fall. Participants who reported a fall or near fall on the calendar but did not call the research assistant were contacted to complete this questionnaire. Events were reclassified, as necessary, based on the participants’ description (e.g. if a participant reported a near fall but, upon interview, it was determined that s/he actually came to rest on a lower level). Physical activity was evaluated using the Physical Activity Scale for Individuals with Physical Disabilities (PASIPD [22]) three times (approximately every 2 months) during the falls monitoring period to obtain an estimate of physical activity. As most falls post-stroke occur while walking [21], the total time spent walking per day was estimated from the
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PASIPD. PASIPD scores and walking times were averaged over the three time points to obtain an estimate of activity in the 6-month period. Statistical analysis For descriptive purposes, participants were classified as non-fallers (no falls reported), single fallers (one fall reported) or multiple fallers (more than one fall reported). Logistic and Poisson regression were conducted to determine the ability of each measure of reactive balance control to predict risk of falls post-discharge. Logistic regression was used to determine the relationship between measures of reactive balance control and probability of being classified as a ‘faller’; that is, the dependent variable was falling status (i.e. ‘faller’ vs ‘non-faller’). Poisson regression was used to determine the relationship between measures of reactive balance control and fall rates. Poisson regression is appropriate when there are multiple events per person, events are statistically rare, and there is a variable follow-up duration for each participant. For Poisson regression, the dependent variable was normalised by determining the number of falls divided by the monitoring duration. Univariate regressions were conducted for each independent variable alone. For quiet standing and walking, the independent variables were: RMS of anteroposterior and medio-lateral COP; contribution of the paretic limb to antero-posterior balance control; between-limb synchronisation; and step length, width and time variability. For reactive stepping (usual-response condition), the independent variables were: frequency of trials where the participant was unable to recover balance by stepping (i.e. either an ‘assist’ or reach-to-grasp response); number of steps; and frequency of ‘slide’ steps. For the encouraged-use condition, the independent variable was frequency of trials where the participant was unable to step with the unblocked limb (i.e. either an attempt to step with the blocked limb or the initial step was a ‘slide’ step with the unblocked limb). Multivariate logistic and Poisson regressions were conducted for those reactive balance measures that were significantly related to falls, controlling for age, stroke severity (National Institutes of Health Stroke Scale), functional balance (Berg Balance Scale) and daily activity (average time spent walking per day). Odds ratios and rate ratios are presented in the paper with the corresponding 95% confidence interval (CI) of the ratio in brackets. The Holm–Bonferroni method was used to correct for multiple comparisons [23]; separate corrections were completed for each analysis (initial α = 0.0045).
Results Between October 2010 and March 2013, 419 individuals were discharged from the hospital; of these, 172 (41%) patients met the inclusion criteria and were invited to participate, and 100 patients agreed to participate in the study. Five patients withdrew prior to completing any falls monitoring;
Please cite this article in press as: Mansfield A, et al. Do measures of reactive balance control predict falls in people with stroke returning to the community? Physiotherapy (2015), http://dx.doi.org/10.1016/j.physio.2015.01.009
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Table 1 Participant characteristics at the time of discharge from inpatient rehabilitation.
Demographic and stroke information Age (years) Sex (n, %) Women Men Type of stroke (n, %) Ischaemic Haemorrhagic Transforming to haemorrhagic Unknown Time post-stroke at discharge (days) Affected hemisphere (n, %) Right Left Both Unknown National Institutes of Health Stroke Scale (score) Falls history and functional balance and mobility Falls prior to stroke (n, %) Berg Balance Scale (score) Prescribed gait aid (n, %) None Cane Rollator or wheeled walker Rollator and cane Walking speed (m/second)
Non-fallers (n = 60)
Single fallers (n = 21)
Multiple fallers (n = 14)
62.9 (14.2)
61.8 (10.5)
62.7 (14.6)
20 (33) 40 (67)
8 (38) 13 (62)
48 (80) 9 (15) 2 (3) 1 (2) 45.1 (24.6)
15 (71) 3 (14) 2 (10) 1 (5) 52.1 (16.3)
13 (93) 1 (7) 0 (0) 0 (0) 56.3 (20.8)
21 (35) 32 (53) 7 (12) 0 (0) 2.8 (2.4)
9 (43) 8 (38) 3 (14) 1 (5) 3.4 (2.6)
6 (43) 5 (36) 3 (21) 0 (0) 2.7 (2.4)
10 (17) 50.4 (8.0)
6 (29) 45.9 (9.6)
4 (29) 48.1 (4.0)
7 (50) 7 (50)
31 (52) 12 (20) 12 (20) 5 (8) 0.87 (0.35)
7 (33) 5 (24) 8 (38) 1 (5) 0.72 (0.40)
2 (14) 5 (36) 4 (29) 3 (21) 0.66 (0.23)
Quiet standing balance control Antero-posterior RMS of COP (mm) Medio-lateral RMS of COP (mm) Paretic limb contribution Between-limb synchronisation
6.1 (3.0) 3.9 (2.8) 0.46 (0.13) 0.82 (0.14)
6.5 (3.9) 4.8 (3.2) 0.45 (0.10) 0.71 (0.33)
6.3 (2.9) 3.8 (2.5) 0.38 (0.12) 0.67 (0.31)
Spatio-temporal gait variability Step length variability (cm) Step width variability (cm) Step time variability (seconds)
2.9 (1.1) 2.3 (0.9) 0.07 (0.19)
3.6 (1.4) 2.2 (1.2) 0.09 (0.10)
3.2 (1.0) 1.7 (0.6) 0.04 (0.02)
Reactive stepping (n = 71) Assists (% trials) Reach-to-grasp reactions (% trials) Number of steps ‘Slide’ steps (% trials) No-step reactions (% trials) Inability to step with the unblocked limb (% trials) Daily activity Time spent walking (hours/day) PASIPD (score)
2.7 (7) 1.8 (7) 2.3 (1) 4.4 (11) 0 20.8 (35)
14.8 (23) 8.5 (20) 2.4 (1) 9.0 (21) 0 39.4 (43)
12.5 (32) 6.5 (14) 2.6 (1) 2.0 (6) 0 38.7 (22)
0.9 (0.6) 9.8 (5.9)
1.0 (0.6) 9.4 (8.3)
0.5 (0.4) 8.5 (4.9)
COP, centre of pressure; PASPID, Physical Activity Scale for Individuals with Physical Disabilities; RMS, root mean square. Values are means with standard deviations in parentheses (continuous/pseudo-continuous variables), or counts with percentages in parentheses (categorical variables).
therefore, 95 participants were included in the analysis. However, only 71 of the 95 participants completed the reactive stepping assessment; therefore, analysis of reactive stepping data is based on 71 participants. Table 1 details participant characteristics at the time of discharge from inpatient rehabilitation. Seven participants were lost to follow-up between 1.8 and 5.5 months after discharge and, therefore, did not complete the full 6-month falls monitoring period. In the
follow-up period, 60 (63%) participants reported no falls, 21 (22%) participants reported one fall, and 14 (15%) participants reported more than one fall. The 35 participants who fell reported a total of 83 falls. The median time between the occurrence of the fall and the interview with the research assistant was 16 days; 29% of falls (27/83) were reported within 7 days. The details of nine falls (11%) were reported with the assistance of a family member. Most falls occurred
Please cite this article in press as: Mansfield A, et al. Do measures of reactive balance control predict falls in people with stroke returning to the community? Physiotherapy (2015), http://dx.doi.org/10.1016/j.physio.2015.01.009
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Table 2 Reactive balance control and odds of falling. Independent variable
Increment
Odds ratio
P-value
Antero-posterior RMS of COP (mm) Medio-lateral RMS of COP (mm) Paretic limb contribution Between-limb synchronisation Step length variability (cm) Step width variability (cm) Step time variability (seconds) Inability to recover by stepping (% trials) Number of steps Frequency of ‘slide’ steps (% trials) Inability to step with unblocked limb (% trials)
1 1 0.1 0.1 1 1 0.01 20 1 20 20
1.0 (0.9 to 1.2) 1.1 (0.9 to 1.3) 0.8 (0.6 to 1.1) 0.8 (0.6 to 1.0) 1.5 (1.0 to 2.3) 0.7 (0.4 to 1.1) 1.0 (0.1 to 15.8) 2.2 (1.1 to 4.2) 1.2 (0.7 to 2.0) 1.3 (0.6 to 2.5) 1.3 (1.0 to 1.7)
0.54 0.21 0.20 0.020 0.033 0.14 0.95 0.023 0.51 0.54 0.048
COP, centre of pressure; RMS, root mean square. Values are point estimates and 95% confidence intervals for the odds ratios (logistic regression) representing the change in odds of falling for each incremental increase in each variable. The odds ratio is for the model including that independent variable alone. As no independent variables were significantly related to increased odds of falling (adjusted α = 0.0045), multivariate analysis was not conducted.
in participants’ homes (51/83, 63%), while walking (26/83, 32%) or transferring/transitioning (23/83, 28%). For 37% of falls (30/83), participants required assistance to get up. Eighteen falls (18/83, 22%) resulted in injuries, with five (5/83, 6%) requiring treatment from a healthcare professional. While the majority of fallers (26/35, 74%) were recommended to use a gait aid, such as a cane or rollator, for indoor and/or community mobility at discharge, only 22% of falls (18/83) occurred when a gait aid was being used. From logistic regression, no reactive balance control variables were related to increased odds of falling when adjusted for multiple comparisons (P > 0.0045; Table 2). Poisson regression revealed that increased RMS of medio-lateral COP, decreased between-limb synchronisation, decreased contribution of the paretic limb to balance control, increased step length and width variability, and increased frequency of encouraged-use trials in which the participant was unable to step with the unblocked limb were related to increased fall rates when adjusted for multiple comparisons (Table 3; P < 0.01). Paretic limb contribution (rate ratio 0.8; 95% CI 0.7 to 1.0; P = 0.011), between-limb synchronisation (rate ratio
0.9; 95% CI 0.8 to 0.9; P < 0.0001), step length variability (rate ratio 1.4; 95% CI 1.2 to 1.7; P = 0.0011) and inability to step with the unblocked limb (rate ratio 1.2; 95% CI 1.0 to 1.3; P = 0.013) remained significantly related to fall rates when controlling for age, stroke severity, functional balance and daily walking activity. Discussion While others have reported a link between functional balance measures and falls post-stroke [3–5], this study demonstrated that specific measures of reactive balance control at discharge from inpatient stroke rehabilitation predict increased fall rates in the 6 months post-discharge into the community among independently ambulating individuals with stroke. These significant relationships were independent of age, stroke severity, functional balance measures and walking activity. Thus, this work provides support for a hypothesised causal link between impaired reactive balance control and increased risk of falls. However, further support for this hypothesis is required from interventional studies.
Table 3 Reactive balance control and fall rates. Independent variable
Increment
Univariate rate ratio
P-value
Antero-posterior RMS of COP (mm) Medio-lateral RMS of COP (mm) Paretic limb contribution Between-limb synchronisation Step length variability (cm) Step width variability (cm) Step time variability (seconds) Inability to recover by stepping (% trials) Number of steps Frequency of ‘slide’ steps (% trials) Inability to step with unblocked limb (% trials)
1 1 0.1 0.1 1 1 0.01 20 1 20 20
1.1 (1.0 to 1.1) 1.1 (1.0 to 1.2) 0.7 (0.6 to 0.9) 0.9 (0.8 to 0.9) 1.2 (1.1 to 1.4) 0.6 (0.4 to 0.8) 0.6 (0.1 to 3.7) 1.1 (0.9 to 1.4) 0.9 (0.7 to 1.2) 1.0 (0.7 to 1.5) 1.3 (1.1 to 1.4)
0.016 0.0066* 0.0008*
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Do measures of reactive balance control predict falls in people with stroke returning to the community? A. Mansfield a,b,c,∗ , J.S. Wong a,b , W.E. McIlroy a,b,c,d , L. Biasin a,b , K. Brunton a,b , M. Bayley a,b,c , E.L. Inness a,b a
Toronto Rehabilitation Institute–University Health Network, Toronto, ON, Canada b University of Toronto, Toronto, ON, Canada c Sunnybrook Health Sciences Centre, Toronto, ON, Canada d University of Waterloo, Waterloo, ON, Canada
Abstract Objective To determine if reactive balance control measures predict falls after discharge from stroke rehabilitation. Design Prospective cohort study. Setting Rehabilitation hospital and community. Participants Independently ambulatory individuals with stroke who were discharged home after inpatient rehabilitation (n = 95). Main outcome measures Balance and gait measures were obtained from a clinical assessment at discharge from inpatient stroke rehabilitation. Measures of reactive balance control were obtained: (1) during quiet standing; (2) when walking; and (3) in response to large postural perturbations. Participants reported falls and activity levels up to 6 months post-discharge. Logistic and Poisson regressions were used to identify measures of reactive balance control that were related to falls post-discharge. Results Decreased paretic limb contribution to standing balance control [rate ratio 0.8, 95% confidence interval (CI) 0.7 to 1.0; P = 0.011], reduced between-limb synchronisation of quiet standing balance control (rate ratio 0.9, 95% CI 0.8 to 0.9; P < 0.0001), increased step length variability (rate ratio 1.4, 95% CI 1.2 to 1.7; P = 0.0011) and inability to step with the blocked limb (rate ratio 1.2, 95% CI 1.0 to 1.3; P = 0.013) were significantly associated with increased fall rates when controlling for age, stroke severity, functional balance and daily walking activity. Conclusions Impaired reactive balance control in standing and walking predicted increased risk of falls post-discharge from stroke rehabilitation. Specifically, measures that revealed the capacity of both limbs to respond to instability were related to increased risk of falls. These results suggest that post-stroke rehabilitation strategies for falls prevention should train responses to instability, and focus on remediating dyscontrol in the more-affected limb. © 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.
Keywords: Accidental falls; Stroke; Rehabilitation; Community; Postural balance
Introduction Risk of falls post-stroke is high; up to 73% of communitydwelling stroke survivors fall in the 6 months after discharge from hospital [1]. This suggests that those at greatest risk ∗ Corresponding author. Address: Toronto Rehabilitation Institute–University Health Network, Research–Mobility, 550 University Ave, Room 11-117, Toronto, ON, Canada M5A 2G2. Tel.: +1 416 597 3422x7831; fax: +1 416 597 3031. E-mail address: [email protected] (A. Mansfield).
are not identified or prepared for the challenges they will encounter in their everyday living environments [2]. Individuals with stroke often have impaired balance control, which may increase the risk of falls. While several prospective studies of community-dwelling adults with stroke demonstrated a link between functional balance measures and falls [3–5], other studies found no differences in these balance measures between fallers and non-fallers [6,7]. There are several limitations to existing predictors of falls available to clinicians. Clinical measures typically assign numerical values to varying levels of performance on tasks
http://dx.doi.org/10.1016/j.physio.2015.01.009 0031-9406/© 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.
Please cite this article in press as: Mansfield A, et al. Do measures of reactive balance control predict falls in people with stroke returning to the community? Physiotherapy (2015), http://dx.doi.org/10.1016/j.physio.2015.01.009
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that challenge an individual’s balance, but are neither able to quantify nor reveal the underlying sources of dyscontrol which make that task challenging. A key factor that ultimately determines whether an individual will fall is the ability to react to a loss of balance [8]. Individuals with stroke have impaired reactive balance control (i.e. the ability to execute appropriate and effective reactions to recover from perturbations to balance) [9–12]. This study aimed to determine if measures of reactive balance control (assessed during quiet standing and walking, and in response to external postural perturbations) predict increased risk of falls for stroke survivors returning to community living following discharge from inpatient rehabilitation. It was hypothesised that impaired reactive balance control in quiet standing and walking, and in response to external postural perturbations would be predictive of increased risk of falls, independent of age, stroke severity, daily walking activity or functional balance measures.
Methods Study design This was a prospective cohort study. Participants with stroke were recruited at discharge from inpatient rehabilitation and followed for up to 6 months post-discharge. The study was approved by the Toronto Rehabilitation Institute Research Ethics Board (Ref. TRI REB No.10-043). Participants provided written informed consent prior to participation. Participants Individuals with stroke attending inpatient rehabilitation at the Toronto Rehabilitation Institute were eligible for the study if they were: (1) assessed in a specialised balance clinic at discharge; (2) discharged home; and (3) able to ambulate independently (i.e. without assistance/supervision of another person, with or without a gait aid) at the time of discharge. The clinic assessment was completed as part of routine practice by all individuals who had sufficient physical, communication and cognitive function to complete the assessment (as determined by the primary treating physiotherapist); therefore, no further exclusion criteria were applied. Predictor variables Measures of reactive balance control were obtained from the clinic assessment. Variables focused on three domains: (1) quiet standing, (2) walking and (3) perturbation-evoked reactive stepping. Additional data were obtained from participants’ hospital charts, including age, sex, type of stroke, time post-stroke, affected hemisphere, pre-morbid falls history, National Institutes of Health Stroke Scale [13] scores, and Berg Balance Scale [14] scores. The National Institute of
Health Stroke Scale is an 11-item scale that provides a gross measure of the effects and severity of stroke, with higher scores indicating more severe strokes. Items assess cognition (level of consciousness, orientation and ability to follow commands), gaze, visual fields, facial palsy, gross motor function in the arm and leg, ataxia, sensation, language, speech, and extinction and inattention. The Berg Balance Scale is a 14item observational rating scale that provides a measure of functional anticipatory balance control (rather than reactive balance control). For participants with bilateral stroke, the more-affected side was identified. Quiet standing Participants stood in a standardised foot position [15] with one foot on each of two force plates for 30 seconds, and were asked to stand as still as possible with their eyes open. Forces and moments were recorded from the force plates at 256 Hz and filtered using a 10-Hz low-pass zero phase lag Butterworth filter prior to processing. The anteroposterior and medio-lateral centres of pressure (COP) were calculated for each force plate separately and for both feet combined. The root mean square (RMS) of total anteroposterior and medio-lateral COP were calculated to provide a measure of overall COP variability. The contribution of the paretic limb to balance control was calculated by dividing the RMS of antero-posterior COP under the more-affected limb by the sum of the RMS of antero-posterior COP under each limb [16,17]; a value of 0.5 indicates that both limbs contribute equally to balance control, 0.5 indicates that the more-affected limb contributes more to balance control. Between-limb synchronisation of antero-posterior COP was calculated by determining the correlation coefficient between the left and right antero-posterior COP [18,19]. Antero-posterior COP was used for the contribution and synchronisation measures as individual-limb medio-lateral COP is less meaningful for overall bipedal balance control [20]. Walking Participants walked across a 4-m-long pressure mat at their usual pace without a walking aid (whenever possible). Participants walked across the mat three to five times such that at least 18 footfalls were recorded. Step length, step width and step time were calculated for each step. The standard deviations of step length, width and time were calculated for each limb separately; variability was calculated as the average of the standard deviations for the left and right limbs. Overall walking speed was also calculated. Reactive stepping A lean-and-release system was used to study reactive stepping [9,10,12]. Participants stood in a standardised foot position [15], and wore a belt around their trunks attached to a beam via a cable. Participants leaned forward such that approximately 10% of body weight was supported by the
Please cite this article in press as: Mansfield A, et al. Do measures of reactive balance control predict falls in people with stroke returning to the community? Physiotherapy (2015), http://dx.doi.org/10.1016/j.physio.2015.01.009
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cable. The cable released unexpectedly, causing them to fall forwards; the magnitude of the perturbation was so great that a reactive step was required to regain stability. Participants were supervised closely by a physiotherapist who provided assistance, if necessary, and a safety harness attached to an overhead track was worn such that participants would not fall to the floor. Five trials were completed in each of two conditions: usual response and encouraged use. In the usualresponse condition, there was no constraint on participants’ stepping reactions. The ‘preferred’ limb was the limb used most frequently to initiate stepping in the usual-response condition. In the encouraged-use condition, the preferred limb was blocked by the physiotherapists’ hand or foot to encourage stepping with the non-preferred limb [11]. Trials were video-recorded. For the usual-response condition, the following outcome measures were obtained: frequency of ‘assists’ (i.e. reliance on physiotherapist or harness to prevent a fall); frequency of attempted reach-to-grasp reactions (i.e. participant reached for and grasped the physiotherapist); number of steps taken to recover balance; and frequency of ‘slide’ steps (i.e. the initial step involved foot movement without lifting the foot completely off the ground [10]). For the encourageduse condition, the frequency of trials in which the participant attempted to step with the blocked limb was determined. Falls and daily activity Participants completed a 6-month falls monitoring period following discharge from inpatient rehabilitation. Participants used fortnightly calendars printed on pre-stamped postcards to indicate if they experienced a fall or near fall each day, and these were mailed back to the study investigators when each calendar was complete. Participants received a monthly study newsletter as a reminder to return their postcards. If participants failed to return a postcard, a research assistant called them to ascertain if they had fallen in the previous 2 weeks. A fall was defined as ‘an event that results in a person coming to rest unintentionally on the ground or other lower level’ [21]. Falls that occurred due to fainting or loss of consciousness were excluded from analysis. Participants who reported a fall or near fall were asked to call the research assistant to complete a short telephone questionnaire in order to determine the circumstances surrounding the fall or near fall. Participants who reported a fall or near fall on the calendar but did not call the research assistant were contacted to complete this questionnaire. Events were reclassified, as necessary, based on the participants’ description (e.g. if a participant reported a near fall but, upon interview, it was determined that s/he actually came to rest on a lower level). Physical activity was evaluated using the Physical Activity Scale for Individuals with Physical Disabilities (PASIPD [22]) three times (approximately every 2 months) during the falls monitoring period to obtain an estimate of physical activity. As most falls post-stroke occur while walking [21], the total time spent walking per day was estimated from the
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PASIPD. PASIPD scores and walking times were averaged over the three time points to obtain an estimate of activity in the 6-month period. Statistical analysis For descriptive purposes, participants were classified as non-fallers (no falls reported), single fallers (one fall reported) or multiple fallers (more than one fall reported). Logistic and Poisson regression were conducted to determine the ability of each measure of reactive balance control to predict risk of falls post-discharge. Logistic regression was used to determine the relationship between measures of reactive balance control and probability of being classified as a ‘faller’; that is, the dependent variable was falling status (i.e. ‘faller’ vs ‘non-faller’). Poisson regression was used to determine the relationship between measures of reactive balance control and fall rates. Poisson regression is appropriate when there are multiple events per person, events are statistically rare, and there is a variable follow-up duration for each participant. For Poisson regression, the dependent variable was normalised by determining the number of falls divided by the monitoring duration. Univariate regressions were conducted for each independent variable alone. For quiet standing and walking, the independent variables were: RMS of anteroposterior and medio-lateral COP; contribution of the paretic limb to antero-posterior balance control; between-limb synchronisation; and step length, width and time variability. For reactive stepping (usual-response condition), the independent variables were: frequency of trials where the participant was unable to recover balance by stepping (i.e. either an ‘assist’ or reach-to-grasp response); number of steps; and frequency of ‘slide’ steps. For the encouraged-use condition, the independent variable was frequency of trials where the participant was unable to step with the unblocked limb (i.e. either an attempt to step with the blocked limb or the initial step was a ‘slide’ step with the unblocked limb). Multivariate logistic and Poisson regressions were conducted for those reactive balance measures that were significantly related to falls, controlling for age, stroke severity (National Institutes of Health Stroke Scale), functional balance (Berg Balance Scale) and daily activity (average time spent walking per day). Odds ratios and rate ratios are presented in the paper with the corresponding 95% confidence interval (CI) of the ratio in brackets. The Holm–Bonferroni method was used to correct for multiple comparisons [23]; separate corrections were completed for each analysis (initial α = 0.0045).
Results Between October 2010 and March 2013, 419 individuals were discharged from the hospital; of these, 172 (41%) patients met the inclusion criteria and were invited to participate, and 100 patients agreed to participate in the study. Five patients withdrew prior to completing any falls monitoring;
Please cite this article in press as: Mansfield A, et al. Do measures of reactive balance control predict falls in people with stroke returning to the community? Physiotherapy (2015), http://dx.doi.org/10.1016/j.physio.2015.01.009
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Table 1 Participant characteristics at the time of discharge from inpatient rehabilitation.
Demographic and stroke information Age (years) Sex (n, %) Women Men Type of stroke (n, %) Ischaemic Haemorrhagic Transforming to haemorrhagic Unknown Time post-stroke at discharge (days) Affected hemisphere (n, %) Right Left Both Unknown National Institutes of Health Stroke Scale (score) Falls history and functional balance and mobility Falls prior to stroke (n, %) Berg Balance Scale (score) Prescribed gait aid (n, %) None Cane Rollator or wheeled walker Rollator and cane Walking speed (m/second)
Non-fallers (n = 60)
Single fallers (n = 21)
Multiple fallers (n = 14)
62.9 (14.2)
61.8 (10.5)
62.7 (14.6)
20 (33) 40 (67)
8 (38) 13 (62)
48 (80) 9 (15) 2 (3) 1 (2) 45.1 (24.6)
15 (71) 3 (14) 2 (10) 1 (5) 52.1 (16.3)
13 (93) 1 (7) 0 (0) 0 (0) 56.3 (20.8)
21 (35) 32 (53) 7 (12) 0 (0) 2.8 (2.4)
9 (43) 8 (38) 3 (14) 1 (5) 3.4 (2.6)
6 (43) 5 (36) 3 (21) 0 (0) 2.7 (2.4)
10 (17) 50.4 (8.0)
6 (29) 45.9 (9.6)
4 (29) 48.1 (4.0)
7 (50) 7 (50)
31 (52) 12 (20) 12 (20) 5 (8) 0.87 (0.35)
7 (33) 5 (24) 8 (38) 1 (5) 0.72 (0.40)
2 (14) 5 (36) 4 (29) 3 (21) 0.66 (0.23)
Quiet standing balance control Antero-posterior RMS of COP (mm) Medio-lateral RMS of COP (mm) Paretic limb contribution Between-limb synchronisation
6.1 (3.0) 3.9 (2.8) 0.46 (0.13) 0.82 (0.14)
6.5 (3.9) 4.8 (3.2) 0.45 (0.10) 0.71 (0.33)
6.3 (2.9) 3.8 (2.5) 0.38 (0.12) 0.67 (0.31)
Spatio-temporal gait variability Step length variability (cm) Step width variability (cm) Step time variability (seconds)
2.9 (1.1) 2.3 (0.9) 0.07 (0.19)
3.6 (1.4) 2.2 (1.2) 0.09 (0.10)
3.2 (1.0) 1.7 (0.6) 0.04 (0.02)
Reactive stepping (n = 71) Assists (% trials) Reach-to-grasp reactions (% trials) Number of steps ‘Slide’ steps (% trials) No-step reactions (% trials) Inability to step with the unblocked limb (% trials) Daily activity Time spent walking (hours/day) PASIPD (score)
2.7 (7) 1.8 (7) 2.3 (1) 4.4 (11) 0 20.8 (35)
14.8 (23) 8.5 (20) 2.4 (1) 9.0 (21) 0 39.4 (43)
12.5 (32) 6.5 (14) 2.6 (1) 2.0 (6) 0 38.7 (22)
0.9 (0.6) 9.8 (5.9)
1.0 (0.6) 9.4 (8.3)
0.5 (0.4) 8.5 (4.9)
COP, centre of pressure; PASPID, Physical Activity Scale for Individuals with Physical Disabilities; RMS, root mean square. Values are means with standard deviations in parentheses (continuous/pseudo-continuous variables), or counts with percentages in parentheses (categorical variables).
therefore, 95 participants were included in the analysis. However, only 71 of the 95 participants completed the reactive stepping assessment; therefore, analysis of reactive stepping data is based on 71 participants. Table 1 details participant characteristics at the time of discharge from inpatient rehabilitation. Seven participants were lost to follow-up between 1.8 and 5.5 months after discharge and, therefore, did not complete the full 6-month falls monitoring period. In the
follow-up period, 60 (63%) participants reported no falls, 21 (22%) participants reported one fall, and 14 (15%) participants reported more than one fall. The 35 participants who fell reported a total of 83 falls. The median time between the occurrence of the fall and the interview with the research assistant was 16 days; 29% of falls (27/83) were reported within 7 days. The details of nine falls (11%) were reported with the assistance of a family member. Most falls occurred
Please cite this article in press as: Mansfield A, et al. Do measures of reactive balance control predict falls in people with stroke returning to the community? Physiotherapy (2015), http://dx.doi.org/10.1016/j.physio.2015.01.009
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Table 2 Reactive balance control and odds of falling. Independent variable
Increment
Odds ratio
P-value
Antero-posterior RMS of COP (mm) Medio-lateral RMS of COP (mm) Paretic limb contribution Between-limb synchronisation Step length variability (cm) Step width variability (cm) Step time variability (seconds) Inability to recover by stepping (% trials) Number of steps Frequency of ‘slide’ steps (% trials) Inability to step with unblocked limb (% trials)
1 1 0.1 0.1 1 1 0.01 20 1 20 20
1.0 (0.9 to 1.2) 1.1 (0.9 to 1.3) 0.8 (0.6 to 1.1) 0.8 (0.6 to 1.0) 1.5 (1.0 to 2.3) 0.7 (0.4 to 1.1) 1.0 (0.1 to 15.8) 2.2 (1.1 to 4.2) 1.2 (0.7 to 2.0) 1.3 (0.6 to 2.5) 1.3 (1.0 to 1.7)
0.54 0.21 0.20 0.020 0.033 0.14 0.95 0.023 0.51 0.54 0.048
COP, centre of pressure; RMS, root mean square. Values are point estimates and 95% confidence intervals for the odds ratios (logistic regression) representing the change in odds of falling for each incremental increase in each variable. The odds ratio is for the model including that independent variable alone. As no independent variables were significantly related to increased odds of falling (adjusted α = 0.0045), multivariate analysis was not conducted.
in participants’ homes (51/83, 63%), while walking (26/83, 32%) or transferring/transitioning (23/83, 28%). For 37% of falls (30/83), participants required assistance to get up. Eighteen falls (18/83, 22%) resulted in injuries, with five (5/83, 6%) requiring treatment from a healthcare professional. While the majority of fallers (26/35, 74%) were recommended to use a gait aid, such as a cane or rollator, for indoor and/or community mobility at discharge, only 22% of falls (18/83) occurred when a gait aid was being used. From logistic regression, no reactive balance control variables were related to increased odds of falling when adjusted for multiple comparisons (P > 0.0045; Table 2). Poisson regression revealed that increased RMS of medio-lateral COP, decreased between-limb synchronisation, decreased contribution of the paretic limb to balance control, increased step length and width variability, and increased frequency of encouraged-use trials in which the participant was unable to step with the unblocked limb were related to increased fall rates when adjusted for multiple comparisons (Table 3; P < 0.01). Paretic limb contribution (rate ratio 0.8; 95% CI 0.7 to 1.0; P = 0.011), between-limb synchronisation (rate ratio
0.9; 95% CI 0.8 to 0.9; P < 0.0001), step length variability (rate ratio 1.4; 95% CI 1.2 to 1.7; P = 0.0011) and inability to step with the unblocked limb (rate ratio 1.2; 95% CI 1.0 to 1.3; P = 0.013) remained significantly related to fall rates when controlling for age, stroke severity, functional balance and daily walking activity. Discussion While others have reported a link between functional balance measures and falls post-stroke [3–5], this study demonstrated that specific measures of reactive balance control at discharge from inpatient stroke rehabilitation predict increased fall rates in the 6 months post-discharge into the community among independently ambulating individuals with stroke. These significant relationships were independent of age, stroke severity, functional balance measures and walking activity. Thus, this work provides support for a hypothesised causal link between impaired reactive balance control and increased risk of falls. However, further support for this hypothesis is required from interventional studies.
Table 3 Reactive balance control and fall rates. Independent variable
Increment
Univariate rate ratio
P-value
Antero-posterior RMS of COP (mm) Medio-lateral RMS of COP (mm) Paretic limb contribution Between-limb synchronisation Step length variability (cm) Step width variability (cm) Step time variability (seconds) Inability to recover by stepping (% trials) Number of steps Frequency of ‘slide’ steps (% trials) Inability to step with unblocked limb (% trials)
1 1 0.1 0.1 1 1 0.01 20 1 20 20
1.1 (1.0 to 1.1) 1.1 (1.0 to 1.2) 0.7 (0.6 to 0.9) 0.9 (0.8 to 0.9) 1.2 (1.1 to 1.4) 0.6 (0.4 to 0.8) 0.6 (0.1 to 3.7) 1.1 (0.9 to 1.4) 0.9 (0.7 to 1.2) 1.0 (0.7 to 1.5) 1.3 (1.1 to 1.4)
0.016 0.0066* 0.0008*
